Development of new chemical and biochemical substances is time-consuming because a number of intermediate substances are traditionally formulated before formulation of a substance with the desired properties is obtained, and formulation of each intermediate substance can takes hours or days. Chemical formulation includes manufacture of traditional organic or polymer substances, as well as the development of small-molecule machinery, sometimes referred to as nanomachinery. Biochemical formulation includes the development and analysis of pharmaceutical substances that affect an individual's quality of life. In addition to the tedious and often error-prone nature of chemical and biochemical formulation, both of these fields face additional difficulties.
Development of chemical substances and nanomachinery, in addition to being time-consuming, can generate potentially dangerous intermediate substances. For example, in attempting to formulate bacteria that consumes crude oil and breaks it down into one or more environmentally-friendly substances, a researcher may formulate a bacterium that breaks crude oil into a number of environmentally-friendly substances and a lethal toxin. Additionally, chemical researchers are faced with the problem of disposing of the intermediate products generated by their research. Other issued faced by designers of nanomachinery is that the target substance may mutate during formulation in response to environmental factors.
Biochemical research, which typically focuses on identifying and selecting compounds having the potential to affect one or more mechanisms thought to be critical in altering specific clinical aspects of a disease processes faces challenges in addition to the ones described above.
Although drug development is typically motivated by research data regarding cellular and subcellular phenomena, the data often considers only an isolated and rather narrow view of an entire system. Such data may not provide an integrated view of the complete biological system. Moreover, the narrow findings reported are not always entirely accurate when translated to the whole body level.
Moreover, current methods of obtaining data for biological processes are even more time-consuming than those associated with chemical processes, because the latter for biochemical substances generally require laboratory experiments that lead to animal experiments and clinical trials. From these trials and experiments, data are obtained which, again, usually focus on a very narrow part of the biological system. Only after numerous costly trial-and-error clinical trials, and constant redesigning of the clinical use of the drug to account for lessons learned from the most recent clinical trial, is a drug having adequate safety and efficacy finally realized. This process of clinical trial design and redesign, multiple clinical trials and, in some situations, multiple drug redesigns requires great expense of time and money. Even then, the effort may not produce a marketable drug. While conclusions may be drawn by assimilating experimental data and published information, it is difficult, if not impossible, to synthesize the relationships among all the available data and knowledge.
The various challenges faced by chemical and biochemical researchers make it desirable to have systems and methods for modeling, simulating, and analyzing biological processes in-silico rather than in-vivo or in-vitro